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Research
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Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification
Shang Liu, Zhongze Cai, Guanting Chen, Xiaocheng Li
[arXiv]
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Understanding the Training and Generalization of Pretrained Transformer for Sequential Decision Making
Hanzhao Wang, Yu Pan, Fupeng Sun, Shang Liu, Kalyan Talluri, Guanting Chen, Xiaocheng Li
[arXiv]
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Uncertainty Estimation and Quantification for LLMs: A Simple Supervised Approach
Linyu Liu, Yu Pan, Xiaocheng Li, Guanting Chen
[arXiv]
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Learning to Make Adherence-Aware Advice
Guanting Chen, Xiaocheng Li, Chunlin Sun, Hanzhao Wang
ICLR 2024 [arXiv]
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Facilitating Battery Swapping Services for Freight Trucks with Spatial-Temporal Demand Prediction
Linyu Liu, Zhen Dai, Shiji Song, Xiaocheng Li, Guanting Chen
NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning [arXiv]
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Fairer LP-based Online Allocation
Guanting Chen, Xiaocheng Li, Yinyu Ye
Under Review [arXiv]
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An Improved Analysis of LP-based Control for Revenue Management
Guanting Chen, Xiaocheng Li, Yinyu Ye
Operations Research [arXiv]
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Unbiased Simulation Estimator for Multivariate Jump-Diffusions
Guanting Chen, Alex Shkolnik, Kay Giesecke
Under Review [SSRN]
An earier version appeared in Proceedings of the Winter Simulation Conference (WSC) 2019 [Link]
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Unbiased Gradient Simulation for Zeroth-order Optimization
Guanting Chen
Proceedings of the Winter Simulation Conference (WSC) 2020 [Link]
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Unbiased Simulation Estimators for Path Integrals of Diffusions
Guanting Chen, Alex Shkolnik, Kay Giesecke
Finalist for Best Contributed Theory Paper
Proceedings of the Winter Simulation Conference (WSC) 2020 [Link]
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An Adaptive State Aggregation Algorithm for Markov Decision Processes
Guanting Chen, Johann Demetrio Gaebler, Matt Peng, Chunlin Sun, Yinyu Ye
Working paper [arXiv]
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